Confession session: Learning from others mistakes

Abshire, Pamela; Bermak, Amine; Berner, Raphael; Cauwenberghs, Gert; Chen, S.; Christen, Jennifer Blain; Constandinou, Timothy G.; Culurciello, Eugenio; Dandin, Marc; Datta, Timir; Delbrück, Tobi; Dudek, Piotr; Eftekhar, Amir; Etienne‐Cummings, Ralph; Indiveri, Giacomo; Law, Man Kay; Linares-Barranco, B.; Tapson, Jonathan; Tang, Wei; Zhai, Yiming

doi:10.1109/iscas.2011.5937774

Cited by 3 publications

(1 citation statement)

References 12 publications

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“…For example, they are too small for standard microfabrication equipment such as resist spinners and mask aligners, and photoresist edge beads can cover the entire chip. [41][42][43] The chip area C determines how far the I/O regions can be separated from the active region, i.e. the barrier distance B.…”

Section: Discussion: Cmos Packagingmentioning

confidence: 99%

Packaging commercial CMOS chips for lab on a chip integration

2014

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Combining integrated circuitry with microfluidics enables lab-on-a-chip (LOC) devices to perform sensing, freeing them from benchtop equipment. However, this integration is challenging with small chips, as is briefly reviewed with reference to key metrics for package comparison. In this paper we present a simple packaging method for including mm-sized, foundry-fabricated dies containing complementary metal oxide semiconductor (CMOS) circuits within LOCs. The chip is embedded in an epoxy handle wafer to yield a level, large-area surface, allowing subsequent photolithographic post-processing and microfluidic integration. Electrical connection off-chip is provided by thin film metal traces passivated with parylene-C. The parylene is patterned to selectively expose the active sensing area of the chip, allowing direct interaction with a fluidic environment. The method accommodates any die size and automatically levels the die and handle wafer surfaces. Functionality was demonstrated by packaging two different types of CMOS sensor ICs, a bioamplifier chip with an array of surface electrodes connected to internal amplifiers for recording extracellular electrical signals and a capacitance sensor chip for monitoring cell adhesion and viability. Cells were cultured on the surface of both types of chips, and data were acquired using a PC. Long term culture (weeks) showed the packaging materials to be biocompatible. Package lifetime was demonstrated by exposure to fluids over a longer duration (months), and the package was robust enough to allow repeated sterilization and re-use. The ease of fabrication and good performance of this packaging method should allow wide adoption, thereby spurring advances in miniaturized sensing systems.

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Section: Discussion: Cmos Packagingmentioning

confidence: 99%

Packaging commercial CMOS chips for lab on a chip integration

2014

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Fun with Asynchronous Vision Sensors and Processing

Delbrück

2012

Computer Vision – ECCV 2012. Workshops and Demonstrations

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Abstract. This paper provides a personal perspective on our group's efforts in building event-based vision sensors, algorithms, and applications over the period [2002][2003][2004][2005][2006][2007][2008][2009][2010][2011][2012]. Some recent advances from other groups are also briefly described.When Mahowald and Mead built the first silicon retina with asynchronous digital output around 1992 [1], conventional CMOS active pixel sensors (APS) were still research chips. It required the investment by industry of about a billion dollars to bring CMOS APS to high volume production. So it is no surprise that while the imager community has been consumed by the megapixel race to make nice photos, cameras that mimic more closely how the eye works have taken a long time to come to a useful form. These "silicon retinas" are much more complex at the pixel level than APS cameras and they pay the price in terms of fill factor and pixel size; machine vision cameras with capability of synchronous global electronic shutter are about 5um. Silicon retina pixels are roughly 10 times the area of a machine vision camera pixel. So why are silicon retinas still interesting? Mostly because of the high cost at the system level of processing the highly redundant data from conventional cameras, and the fixed latencies imposed by the frame intervals. High performance activity driven event-based sensors could greatly benefit applications in real time robotics, where just as in nature, latency and power are very important [2,5,9,10].

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